Prognostic value of DCE-MRI in breast cancer patients undergoing neoadjuvant chemotherapy: a comparison with traditional survival indicators

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• 作者：Martin D. Pickles ; Martin Lowry ; David J. Manton ; Lindsay W. Turnbull
• 关键词：Breast cancer ; DCE ; MRI ; Magnetic resonance imaging ; Prognosis ; Survival
• 刊名：European Radiology
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：25
• 期：4
• 页码：1097-1106
• 全文大小：597 KB
• 参考文献：1. Connolly, RM, Stearns, V (2013) Current approaches for neoadjuvant chemotherapy in breast cancer. Eur J Pharmacol 717: pp. 58-66 CrossRef
  2. Kaufmann, M, Hortobagyi, GN, Goldhirsch, A (2006) Recommendations from an international expert panel on the use of neoadjuvant (primary) systemic treatment of operable breast cancer: An update. J Clin Oncol 24: pp. 1940-1949 CrossRef
  3. van de Hage JH, van de Velde CCJH, Mieog SJSD (2007) Preoperative chemotherapy for women with operable breast cancer. Cochrane Database Syst Rev Issue 2. Art. No.:CD005002. DOI: 10.1002/14651858.CD005002.pub2 .
  4. American Cancer Society (2014) Breast cancer survival rates by stage. [Online]. Available at: http://www.cancer.org/cancer/%20breastcancer/detailedguide/breast-cancer-survival-by-stage [Accessed: 4 February 2014].
  5. Padhani, AR, Khan, AA (2010) Duffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy. Target Oncol 5: pp. 39-52 CrossRef
  6. Koo, HR, Cho, N, Song, IC (2012) Correlation of perfusion parameters on dynamic contrast-enhanced MRI with prognostic factors and subtypes of breast cancer. J Magn Reson Imaging 36: pp. 145-151 CrossRef
  7. Bone, B, Szabo, BK, Perbeck, LG, Veress, B, Aspelin, P (2003) Can contrast-enhanced MR imaging predict survival in breast cancer?. Acta Radiol 44: pp. 373-378 CrossRef
  8. Partridge, SC, Gibbs, JE, Essermann, LJ (2005) MRI measurements of breast tumour volume predict response to neoadjuvant chemotherapy and recurrence-free survival. Am J Roentgenol 184: pp. 1774-1781 CrossRef
  9. Johansen, R, Jensen, LR, Rydland, J (2009) Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI. J Magn Reson Imaging 29: pp. 1300-1307 CrossRef
  10. Pickles, MD, Manton, DJ, Lowry, M, Turnbull, LW (2009) Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy. Eur J Radiol 71: pp. 498-505 CrossRef
  11. Heldahl, MG, Bathen, TF, Rydland, J (2010) Prognostic value of pretreatment dynamic contrast-enhanced MR imaging in breast cancer patients receiving neoadjuvant chemotherapy: Overall survival prediction from combined time course and volume analysis. Acta Radiol 6: pp. 604-612 CrossRef
  12. Li, SP, Makris, A, Beresford, MJ (2011) Use of dynamic contrast-enhanced MR imaging to predict survival in patients with primary breast cancer undergoing neoadjuvant chemotherapy. Radiology 260: pp. 68-78 CrossRef
  13. Tuncbilek, N, Tokatli, F, Altaner, S (2012) Prognostic value DCE-MRI parameters in predicting factor disease free survival and overall survival for breast cancer patients. Eur J Radiol 81: pp. 863-867 CrossRef
  14. Dietzel, M, Zoubi, R, Vag, T (2013) Association between survival in patients with primary invasive breast cancer and computer aided MRI. J Magn Reson Imaging 37: pp. 146-155 CrossRef
  15. Jones, EF, Sinha, SP, Newitt, DC (2013) MRI enhancement in stromal tissue surrounding breast tumours: Association with recurrence free surivival following neoadjuvant chemotherapy. Plos One 8: pp. 1-8
  16. Yi, A, Cho, N, Im, S-A (2013) Survival outcomes of breast cancer patients who receive neoadjuvant chemothe
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Imaging and Radiology
  Diagnostic Radiology
  Interventional Radiology
  Neuroradiology
  Ultrasound
  Internal Medicine
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-1084

文摘

Objectives To determine associations between dynamic contrast-enhanced MR imaging (DCE-MRI) parameters and survival intervals in patients with locally advanced breast cancer treated with neoadjuvant chemotherapy (NAC), surgery, and adjuvant therapies. Further, to compare the prognostic value of DCE-MRI parameters against traditional survival indicators. Methods DCE-MRI and MR tumour volume measures were obtained prior to treatment and post 2nd NAC cycle. To demonstrate which parameters were associated with survival, Cox’s proportional hazards models (CPHM) were employed. To avoid over-parameterisation, only those MR parameters with at least a borderline significant result were entered into the final CPHM. Results When considering disease-free survival positive axillary nodal status (hazard ratio [HR] 6.79), younger age (HR 3.37), negative oestrogen receptor status (HR 3.24), pre-treatment Maximum Enhancement Index (MaxEI) (HR 6.51), and percentage change in MaxEI (HR 1.02) represented the retained CPHM covariates. Similarly, positive axillary nodal status (HR 11.47), negative progesterone receptor status (HR 4.37) and percentage change in AUC90 (HR 1.01) represented the retained predictive variables for overall survival. Conclusions Multivariate survival analysis has demonstrated that DCE-MRI parameters obtained prior to NAC and/or post 2nd cycle can provide independent prognostic information that can complement traditional prognostic indicators available prior to treatment. Key points -MR-derived DCE-MRI parameters obtained prior to treatment have prognostic value. -Early treatment-induced reductions in DCE-MRI parameters represents a positive prognostic indicator. -DCE-MRI parameters provide independent prognostic information that can complement traditional prognostic indicators.